Understanding the Role of Micro-Blogging in B-Learning Activities: Kelluwen Experiences in Chilean Public Schools

Scheihing, Eliana; Vernier, Matthieu; Guerra, Julio; Born, Javiera; Cárcamo, Luis

doi:10.1109/tlt.2017.2714163

Cited by 2 publications

(2 citation statements)

References 36 publications

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“…Besides fully online learning environments, blended-learning formats also provide opportunities for students to engage in collaborative learning. For example, Scheihing et al (2018) studied a microblogging platform to identify differences in student interaction patterns. In classroom settings, transcript data from video recordings can be used to automate classifications of classroom discourse structures.…”

Section: Mesolevel Big Datamentioning

confidence: 99%

Mining Big Data in Education: Affordances and Challenges

Fischer

Pardos

Baker

et al. 2020

Review of Research in Education

274

138

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The emergence of big data in educational contexts has led to new data-driven approaches to support informed decision making and efforts to improve educational effectiveness. Digital traces of student behavior promise more scalable and finer-grained understanding and support of learning processes, which were previously too costly to obtain with traditional data sources and methodologies. This synthetic review describes the affordances and applications of microlevel (e.g., clickstream data), mesolevel (e.g., text data), and macrolevel (e.g., institutional data) big data. For instance, clickstream data are often used to operationalize and understand knowledge, cognitive strategies, and behavioral processes in order to personalize and enhance instruction and learning. Corpora of student writing are often analyzed with natural language processing techniques to relate linguistic features to cognitive, social, behavioral, and affective processes. Institutional data are often used to improve student and administrational decision making through course guidance systems and early-warning systems. Furthermore, this chapter outlines current challenges of accessing, analyzing, and using big data. Such challenges include balancing data privacy and protection with data sharing and research, training researchers in educational data science methodologies, and navigating the tensions between explanation and prediction. We argue that addressing these challenges is worthwhile given the potential benefits of mining big data in education.

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Section: Mesolevel Big Datamentioning

confidence: 99%

Mining Big Data in Education: Affordances and Challenges

Fischer

Pardos

Baker

et al. 2020

Review of Research in Education

274

138

View full text Add to dashboard Cite

show abstract

“…B-Learning has been proven to have positive effects on students' satisfaction in different areas of learning [71,88]. It is for this reason that a B-Learning setting with an experimental or practical approach has been employed in some of the related studies [8,30,34,37] and in MiniBool, with the objective of reaffirming the knowledge acquired in classes, thus avoiding the problems of communication, association, and teamwork reported in Reference [81] when only a technology-mediated approach is employed.…”

Section: Blended Learningmentioning

confidence: 99%

Using web‐based gamified software to learn Boolean algebra simplification in a blended learning setting

Jiménez-Hernández

Oktaba

Díaz-Barriga

et al. 2020

Comp Applic In Engineering

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One of the fundamental topics in the education of students enrolled in computer-related degrees is that of Boolean algebra. This is because it allows the expression of several problems related to digital design, artificial intelligence, databases, compilers, and formal languages, among others, as a sequence of Boolean operations and variables, which can be dealt with by using Boolean algebra methods to optimize algorithms, minimize digital components, and so forth. This study presents a piece of web-based software, denominated as MiniBool, which has been developed with the objective of supporting the learning of Boolean algebra in a blended learning setting. This educational proposal gives students the opportunity to reinforce learning at any time and in any place. It additionally increases the learners' motivation by including gamification, through the use of a ranking that shows the students' level of participation. MiniBool was evaluated by means of a formal experiment, which was carried out with Discrete Mathematics students at a higher education institution in Mexico, where two groups were formed randomly: A control group, whose members attended classes and reinforced their knowledge in a traditional manner with a pencil and paper, and an experimental group, which learned in a blended learning context, receiving the same classes as the control group, but reinforcing what they had learned using MiniBool. The statistical results obtained indicate that the use of MiniBool has a positive and motivating effect on learning and that a greater academic performance is achieved than when the traditional teaching-learning method is applied.

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Understanding the Role of Micro-Blogging in B-Learning Activities: Kelluwen Experiences in Chilean Public Schools

Cited by 2 publications

References 36 publications

Mining Big Data in Education: Affordances and Challenges

Mining Big Data in Education: Affordances and Challenges

Using web‐based gamified software to learn Boolean algebra simplification in a blended learning setting

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